Self-Driving Cars Can’t See Without Their Eyes

My short film above, “Their Eyes,” spotlights the invisible, human work behind A.I. In it I explore the daily lives of ...
IEEE

MalSSL—Self-Supervised Learning for Accurate and Label-Efficient Malware Classification

Abstract: Malware classification with supervised learning requires a large dataset, which needs an expensive and time-consuming labeling process. In this paper, we explore the efficacy of ...

Mapping AI Potential: Separating Hype From Real Business Impact

A prediction that looks plausible but diverges from reality can create high-risk, even catastrophic situations in driving ...

AI revolutionises sleep disorder diagnosis: IIITH leads breakthroughs

Hyderabad: Artificial Intelligence (AI) is transforming the way sleep disorders are diagnosed, with researchers at the ...
IEEE

Weak Augmentation Guided Relational Self-Supervised Learning

Abstract: Self-supervised Learning (SSL) including the mainstream contrastive learning has achieved great success in learning visual representations without data annotations. However, most methods ...
Vehiclesuggest

Tesla’s Full Self-Driving Fleet Nears 7 Billion Miles, Cementing Its Lead in Real-World AI Training

Tesla’s Full Self-Driving (Supervised) is getting close to a milestone that not many autonomous driving programs can match.
pv magazine Australia

Machine-learning models identify hidden physical defects in solar arrays

The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Mirage News

Vision Model Maps Tree Growth with Sub-Meter Precision

Forests and plantations play a vital role in carbon sequestration, yet accurately monitoring their growth remains costly and labor-intensive ...

Stony Brook University Develops Machine Learning Models that Predict PV System Underperformance on Heterogeneous Portfolios

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...

insitro Validates AI-Enabled POSH Platform in Nature Communications, Bridging Critical Gap in Drug Discovery

AI therapeutics company built on causal biology, today announced the publication of research in Nature Communications validating its POSH (Pooled Optical Screening in Human cells) platform. The study ...